tbuckley/cabot-search huggingface dataset:
ARC-10: A phase 3 study to evaluate zimberelimab + domvanalimab versus pembrolizumab in front-line, PD-L1-high, locally advanced or metastatic non–small-cell lung cancer.
Authors: Christos Chouaid, Gwo Fuang Ho, Yotsawaj Runglodvatana, Xian He, Christoph Matthias Ahlers, Debbie Pomponio, Trever Todd, Thao Dang, Jarushka Naidoo
Journal: Journal of Clinical Oncology (2023)

TPS9148 Background: Despite improvements in the management of locally advanced or metastatic non–small cell lung cancer (NSCLC) from programmed cell death/ligand protein 1 (PD-[L]1) inhibition, there remains an unmet need for improved treatment options. PD-L1 expression is a known biomarker of response to anti–PD-L1 therapies in metastatic NSCLC. The combination of PD-1 inhibition with inhibition of the immunosuppressive T cell Immunoglobulin and ITIM domain (TIGIT) pathway is associated with improved response and prolonged progression-free survival in patients with advanced NSCLC. Domvanalimab (dom) is an Fc-silent humanized IgG1 monoclonal antibody (mAb) that blocks TIGIT, thereby reducing immunosuppression of T/natural killer (NK) cells and promoting antitumor activity. Zimberelimab (zim) is an mAb that binds to PD-1 on T/NK cells, preventing PD-L1-mediated immunosuppressive effects and resulting in tumor cell death. This phase 3 study will investigate the efficacy and safety of combination therapy with dom + zim compared with pembrolizumab monotherapy in patients with PD-L1-high NSCLC. Methods: ARC-10 (NCT04736173) is a global, phase 3, randomized, multicenter, open-label study. Eligible patients are adults with histologically confirmed, treatment-naive, locally advanced or metastatic, squamous or non-squamous NSCLC with ≥1 measurable lesion(s) per Response Evaluation Criteria in Solid Tumors (RECIST) v1.1, high expression of PD-L1 (tumor cells [TC] ≥50%), and an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1. Patients must not have genomic tumor aberrations for which targeted therapies are approved and available (eg, EGFR, ALK, ROS, BRAF, NTRK). Approximately 600 patients will be randomized 1:1 to receive combination therapy with dom + zim (dom 1200 mg intravenous [IV] once every 3 weeks [Q3W] + zim 360 mg IV Q3W) or pembrolizumab monotherapy (200 mg IV Q3W) for 21-day cycles until disease progression, intolerance, or a maximum of 35 cycles. Randomization will be stratified by ECOG performance status (0 vs 1), geographical region (Asia vs non-Asia), and histology (squamous vs non-squamous). The primary efficacy endpoint is overall survival. Secondary efficacy endpoints include blinded independent central review of progression-free survival and confirmed overall response rate according to RECIST v1.1. Safety endpoints include the presence of treatment-emergent adverse events and laboratory parameters. Health-related quality of life will be assessed by measuring the time to first symptom deterioration in the NSCLC-Symptom Assessment Questionnaire total score. Study recruitment is planned in Asia, North and South America, Africa, and Europe. Clinical trial information: NCT04736173 .
Types of work young adults perform to adjust to a cancer diagnosis and treatment.
Authors: Lauren Victoria Ghazal, Nicholas Iannarino, Josephine Cyers
Journal: Journal of Clinical Oncology (2023)

e24179 Background: Patients and their caregivers perform work (i.e., demanding and arduous labor that takes resources and coordination to address) to manage their illness, relationships, and lives. A growing body of psychosocial research has investigated the communication work performed by young adults (18-39 years old at diagnosis; YAs) and their caregivers as they adjust to cancer treatment and survivorship. However, to our knowledge, no studies have examined how the four types of work identified through Theory of Illness Trajectories (i.e., everyday, illness-related, biographical, and communication) interact within cancer survivorship. Thus, the study purpose was to investigate how and why YAs describe their efforts to manage life along the cancer trajectory as work or labor. Methods: We conducted a qualitative secondary analysis leveraging three separate qualitative interview datasets that sought to describe and explain similar psychosocial aspects of the YA cancer experience. Two specific interview questions: 1) “What advice would you give to another person your age who received a similar diagnosis?” and 2) “What did you learn from your cancer experience that you wish you knew when you were diagnosed?” shaped our thematic analysis. We applied the Theory of Illness Trajectories in the open coding phase, where everyday-life work referred to recurring existing responsibilities (e.g., employment, childcare); illness work related to cancer-management tasks like taking medication and seeing physicians; biographical work involved one’s cognitive efforts to reconstruct their identity, and communication work involved the demanding use of communication to manage identities, share information, or solicit support. During axial coding, each author reviewed one-third of the data individually, making note of units that could be classified as themes related to each type of work. Results: A total of 112 participants completed qualitative interviews across the three studies. Most (71%) were female, and mean age was 26 years. Most received a diagnosis of lymphoma (33.0%), leukemia (17.9%), and breast cancer (11.6%). Data analyses are still ongoing; we are currently meeting regularly to reach consensus on our axial codes. Our final abstract will include findings from our selective coding phase, which will allow us to examine comparisons and interactions between types of work. Conclusions: Additional goals of our innovative qualitative secondary analysis are to a) to identify the most salient subtypes of biographical, illness-related, everyday, and communication work in the YA cancer context and b) to better understand how the four types of work described by theory of illness trajectories interact and whether they facilitate or hinder the performance of additional types of work.
Exploratory study investigating the efficacy and safety of olanzapine prophylaxis for opioid-induced nausea and vomiting (JORTC-PAL20).
Authors: Eriko Satomi, Ayaka Ishikawa, Sayaka Arakawa, Hiroto Ishiki, Koji Amano, Tomomi Kobayashi, Naomi Sakiyama, Ryo Otsuka, Makoto Maeda, Hironobu Hashimoto, Shunsuke Oyamada, Keisuke Ariyoshi, Kota Kihara, Akio Mizushima
Journal: Journal of Clinical Oncology (2023)

TPS12151 Background: In opioid therapy for cancer pain, it is essential to manage opioid-related adverse effects. Opioid-induced nausea and vomiting (OINV) is common, occurring in 20–40% of patients during initial opioid treatment or after opioid doses are increased. Tolerance to OINV develops within a few days to a week. In patients with cancer, OINV results in decreased quality of life as well as failure to relieve pain due to poor opioid adherence, thus increasing the psychological barriers to opioid use. Therefore, antiemetics are used for OINV prophylaxis, but their efficacy and safety in this context have not yet been fully elucidated. Olanzapine is a promising antiemetic for prophylaxis against nausea and vomiting induced by highly emetogenic chemotherapy, and it is less likely to cause extrapyramidal symptoms than haloperidol and prochlorperazine. We are conducting this exploratory study to evaluate the efficacy and safety of olanzapine prophylaxis against OINV. Methods: This single-arm, single-center exploratory study will evaluate the prophylactic antiemetic efficacy and safety of olanzapine (5 mg PO once a day for 5 days) in patients with cancer pain reserving initial regular opioid therapy. Thirty-five patients will be enrolled. This study was designed to provide preliminary efficacy data, with a primary objective of assessing the proportion of patients who achieved complete control (CC) of OINV during 120 hours of opioid treatment. CC was defined as the absence of emetic episodes, the lack of a need for rescue medication to treat nausea, and minimal or no nausea (3 or less on an 11-point categorical scale). Secondary endpoints include the following: the complete response (CR) rate, defined as the percentage of patients with no emetic episodes and no rescue medication use; the total control (TC) rate, defined as the percentage of patients with no emetic episodes, no rescue medication use, and no nausea during the 120 hours of opioid treatment; the time from opioid initiation to the first emetic episode; the time from opioid initiation to the first administration of a rescue antiemetic; the time to treatment failure, defined as the time from opioid initiation to the first emetic episode or to the administration of a rescue antiemetic; the number of emetic episodes; the levels of nausea, anorexia, sleepiness, pain, and fatigue, all determined using a numerical rating scale (0–10); the impact of antiemetic therapy on daily life severity and patient satisfaction, determined using a 7-grade categorical scale; and adverse events graded by PRO-CTCAE ver.1.0 and CTCAE ver. 5.0. The study is currently open, and 25 patients have been enrolled at time of abstract submission. Clinical trial information: jRCTs031220008 .
Antitumor regimens with gemcitabine are safe for tumor patients with COVID-19.
Authors: Yuanqiang Wu, Weini Quan, Jinan Ma, Zhenjiang Li
Journal: Journal of Clinical Oncology (2023)

e18064 Background: COVID-19 infection is a worldwide health threatening disease, especially for malignant tumor patients. Systemic antitumor therapies may slower the body to clear virus, which results in delayed recovery from COVID-19. Thus, present guidelines or expert consensuses recommend to postpone antictumor therapies, which would unquestionablely retard treatment cycle and reduce therapeutic effect.Gemcitabine is a nucleoside analogue, which has shown antiviral activity as well as anticancer effect. Therefore, we assume that antitumor regimens with gemcitabine are also able to control COVID-19 reproduction. Such “kill two birds with one stone” regimen aims to not delay both anticancer treatment and COVID-19 turning negative. Methods: Four newly pathologically diagnosed advanced tumor patients from Department of Oncology, Second Xiangya Hospital, Central South University were collected, including three nasopharyngeal carcinoma (NPC) patients and one non-small cell lung cancer (NSCLC) patient. All of them were asymptomaticly infected with COVID-19 recently. Anticancer regimens with gemcitabine were adopted as initial treatment for these patiens. Three patients with NPC received gemcitabine combined with cisplatin (gemcitabine 1g/㎡ on day 1 and 8, cisplatin 25mg/㎡ from day 1 to 3).The patient with NSCLC accepted gemcitabine and PD-1 inhibitor (gemcitabine 1g/㎡ on day 1 and 8,tislelizumab 100mg on day 1 and 8). Throat swabs were performed to test the COVID-19 nucleic acid on day 1, 5, 9 and 21 during treatment. Results: Four patients are all middle-aged males of 43-59 years old. Their COVID-19 nucleic acid tests were positive on day 1 before infusing any drugs.The cycle count threshold (CT) of nucleic acid did not go down but gradually went up during antitumor treatment.Patients showed no COVID-19 related symptom during the whole treatment cycle. There were no greater than or equal to grade 3 adverse evens (AEs). Treatment related AEs included one patient with grade 2 leukopenia, and one patient with grade 2 fever. All patients normally finished the first anticancer cycle and successfully went to the second cycle. Conclusions: Antitumor regimens with gemcitabine is safe for patients both with manignancy and COVID-19. Cancer patients with COVID-19 can accept gemcitabine-related therapy as soon as possible intead of waiting until COVID-19 nucleic acid becoming negative.
Phase 3 study of durvalumab combined with oleclumab or monalizumab in patients with unresectable stage III NSCLC (PACIFIC-9).
Authors: Fabrice Barlesi, Sarah B. Goldberg, Helen Mann, Aarthi Gopinathan, Michael David Newton, Charu Aggarwal
Journal: Journal of Clinical Oncology (2023)

TPS8610 Background: Based on the findings of the phase 3 PACIFIC trial, durvalumab as consolidation therapy is the standard of care for patients with unresectable Stage III NSCLC and no disease progression following chemoradiotherapy (CRT; the PACIFIC regimen). However, further improvements in outcomes are needed for this population and, to build upon the backbone of PD-L1 inhibition with durvalumab, immunotherapy combinations including anti-TIGIT, anti-CD73, and anti-NKG2a monoclonal antibodies (mAbs) are now being explored. Two potential candidates, oleclumab and monalizumab, have demonstrated encouraging clinical activity in a randomized, phase 2 trial when combined with durvalumab in this setting. Oleclumab (MEDI9447) is a human IgG1λ mAb that inhibits the function of CD73, to reduce extracellular adenosine production and thus promote antitumor immunity. Monalizumab (IPH2201) is a first-in-class, humanized, IgG4 mAb that prevents NKG2A from binding to HLA-E, which reduces inhibition of natural killer and CD8+ T cells. The combination of each of these molecules with durvalumab consolidation therapy was evaluated in the phase 2 COAST study (NCT03822351). In COAST (n = 189), patients receiving combination therapy reported numerically higher objective response rates (durvalumab plus oleclumab: 30.0%; durvalumab plus monalizumab: 35.5%; durvalumab monotherapy: 17.9%) and prolonged progression-free survival versus durvalumab alone, with no new/significant safety signals (Herbst, et al. 2022). Thus, the combination of oleclumab or monalizumab with consolidative durvalumab warrants further evaluation in a phase 3 trial. Methods: PACIFIC-9 (NCT05221840) is a phase 3, double-blind, placebo-controlled, randomized, international trial. Eligible patients (age ≥18 years) must have EGFR/ALK wild-type unresectable Stage III NSCLC, a WHO performance status of 0/1, documented PD-L1 status, and must not have progressed following ≥2 cycles of definitive, platinum-based concurrent CRT. Approximately 999 patients will be randomized (1:1:1) to receive up to 12 months of treatment (in 28-day cycles) with durvalumab plus either oleclumab (Arm A); monalizumab (Arm B); or placebo (Arm C). The primary endpoint is progression-free survival (RECIST v1.1) by blinded independent central review (BICR). Overall survival is a key secondary endpoint. Other secondary endpoints include objective response rate and duration of response (RECIST v1.1; BICR), patient-reported outcomes, PD-L1 expression on tumor cells relative to efficacy outcomes, and safety/tolerability (CTCAE v5.0). Trial enrollment is ongoing. Previously presented at the World Conference on Lung Cancer (WCLC) 2022, FPN (Final Publication Number): P1.10-01, Fabrice Barlesi et al. Clinical trial information: NCT05221840 .
Distinguishing enchondroma from low-grade chondrosarcoma using a multi-stage deep learning model for patient radiographs and histopathology.
Authors: Logan Nye, Hamid Ghaednia, Joseph H. Schwab
Journal: Journal of Clinical Oncology (2023)

e23500 Background: Enchondroma and low-grade (grade 1) chondrosarcoma are cartilaginous tumors of the peripheral bone. Enchondroma is benign, requiring only routine clinical monitoring. Chondrosarcoma is malignant, demanding prompt and aggressive treatment to prevent metastasis. Despite drastically different treatment protocols, these tumors are histologically and radiographically similar, making them difficult to tell apart. Even specialized treatment, years of experience, and access to both imaging modalities, pathologists and radiologists have reported low reliability in distinguishing between these two tumors. Better diagnostic and grading strategies are needed for these lesions. In this study, we propose a two-stage computer vision framework for distinguishing enchondroma from low-grade chondrosarcoma using deep learning. Methods: Our team compiled a ground truth dataset of radiographic and histological images from the annotated records of Dr. Henry Jaffe, a pioneering authority in musculoskeletal pathology. From his records, 55 cases of low-grade chondrosarcoma and 19 cases of enchondroma containing both radiology and histology imaging were identified and included. Radiographs and histology samples corresponding to the same individual were paired together to create 290 paired images of enchondroma and 318 paired images of low-grade chondrosarcoma (pair = 1 histology + 1 radiograph). These image pairings were randomly split into training (~80%) or validation (~20%) groups, excepting minimal reallocations to prevent leakage between training and validation data. All images were preprocessed and augmented for improved model training. Image pairings (one histology image, one radiograph) corresponding to the same patient case were passed through separate VGG16 models pre-trained on ImageNet weights. These models produced two feature vectors as outputs, which were concatenated and subsequently passed through a second-stage binary classification network to predict tumor identity. Results: After 17 epochs, the model recorded training loss and accuracy of 0.6723 and 0.7583, and validation loss and accuracy of 0.7362 and 0.7373, respectively – an improvement upon diagnostic accuracies reported in previous studies. Conclusions: We have created a two-stage deep learning model that predicts whether patient radiographs and histology show enchondroma or low-grade chondrosarcoma. The trained model’s validation accuracy of 73.7% improves upon past reported methods. This suggests that computer vision methods that utilize multiple imaging modalities might augment physicians' capability to discriminate between these two tumor types.
Healthcare access dimensions and uterine cancer survival: A National Cancer Database study.
Authors: Mary Katherine Anastasio, Anjali Gupta, Tomi F. Akinyemiju, Rebecca A. Previs
Journal: Journal of Clinical Oncology (2023)

5594 Background: Racial disparities persist throughout the continuum of care for Black patients with uterine cancer. Few studies have evaluated how multiple dimensions of healthcare access (HCA) contribute to these disparities in patients who present at an advanced stage and meet criteria for adjuvant therapy. Methods: Patients with Stage III-IV uterine cancer between 2004-2015 who received adjuvant therapy with complete sociodemographic and other relevant covariate data were identified in the National Cancer Database (NCDB). Race and ethnicity were defined as non-Hispanic (NH)-Black, Hispanic, and NH-White. Healthcare access dimensions of affordability, availability and accessibility were measured using variables defined in the NCDB. Overall survival was analyzed using Kaplan-Meier curves, log-rank test, and multivariable Cox proportional hazard models. Results: The study cohort included 43,134 patients: 78.8% NH-White, 15.3% NH-Black, and 5.9% Hispanic. Compared to NH-White and Hispanic patients, NH-Black patients were more likely to have Type II (75.6% vs. 53.9% and 55.4%) and Stage IV disease (40.8% vs. 30.7% and 32.3%). NH-Black patients were more likely to receive chemotherapy alone (53.5% vs. 43.1% and 46.2%) compared to NH-White and Hispanic patients. NH-Black patients were the most likely to have government funded insurance (58.6% vs. 50.3% and 50.4%) and live in the lowest income quartile (46.4% vs. 14.2% and 29.9%) compared to NH-White and Hispanic patients. NH-Black patients had a significantly higher risk of death than NH-White patients when adjusting for demographic/clinical characteristics and all three healthcare access dimensions (HR 1.29; 95% CI 1.24, 1.34). Conclusions: Healthcare access affordability predicts survival but does not fully explain racial disparities in survival rates of patients with advanced stage uterine cancer. NH-Black patients are more likely to have aggressive disease, receive chemotherapy alone, and have worse survival than NH-White patients regardless of pathogenic subtype. Investigating additional healthcare access dimensions may be critical to addressing disparities in uterine cancer.
Predicting therapy-induced cardiomyopathy in long-term survivors of childhood cancer: A report from the St. Jude Lifetime Cohort (SJLIFE) and the Childhood Cancer Survivor Study (CCSS).
Authors: Kateryna Petrykey, Huiqi Wang, Stephanie B Dixon, Cindy Im, Matthew J. Ehrhardt, Daniel A. Mulrooney, Noha Sharafeldin, Xuexia Wang, John L. Jefferies, Paul Burridge, Kevin C. Oeffinger, Maria Monica Gramatges, Smita Bhatia, Leslie L. Robison, Kirsten K. Ness, Melissa M. Hudson, Eric Jessen Chow, Gregory T. Armstrong, Yutaka Yasui, Yadav Sapkota
Journal: Journal of Clinical Oncology (2023)

12018 Background: Cancer-therapy-induced cardiomyopathy (CCM) is the leading noncancer cause of mortality among long-term survivors of childhood cancer, the prevalence of which increases with age. Early identification of survivors at risk provides opportunities for targeted prevention strategies. Here, we developed and validated a clinically applicable CCM prediction model based on survivor characteristics, treatment exposures and inherited genetic variation among long-term survivors of childhood cancer. Methods: Long-term survivors from SJLIFE (training cohort; n = 3,350; median age 34 years, range 8-72 years) and CCSS (validation cohort; n = 7,008; median age 36 years, range 11-64 years) were assessed by the five different general population polygenic risk scores (multiPRS) for dilated cardiomyopathy, hypertrophic cardiomyopathy, heart failure, ejection fraction and left ventricular end systolic volume. Multivariable logistic regression was used to predict 15-year risk of the CCM (defined as CTCAE grade ≥3 cardiomyopathy requiring heart failure medications or heart transplantation or leading to death). Model performance was assessed by the area under the receiver operating characteristic curve (AUC). Results: CCM was clinically identified in 150 (4.5%) SJLIFE and self-reported in 156 (2.1%) CCSS survivors, respectively. AUC of clinical models with attained age, sex, age at primary cancer diagnosis, cumulative anthracycline dose, mean heart radiation dose (heart RT), and genetic ancestry was 0.81 (95% CI, 0.78-0.85) in SJLIFE and 0.78 (95% CI, 0.74-0.81) in CCSS. Inclusion of cardiovascular risk factors (hypertension, dyslipidemia, and diabetes) significantly increased AUC to 0.83 (95% CI, 0.80-0.87; P= 0.011; SJLIFE) and 0.84 (95% CI, 0.80-0.87; P&lt; 0.001; CCSS). The addition of the multiPRS further provided significant but modest increases in AUC in SJLIFE (0.84; 95% CI, 0.81-0.87; P= 0.022) and CCSS (0.85; 95% CI, 0.81-0.88; P= 0.031). In low-risk survivors (exposed to &lt; 100 mg/m 2 anthracyclines and &lt; 15 Gray heart RT), we observed a possibly larger magnitude AUC increase after adding multiPRS, 0.73 (95% CI, 0.65-0.82) to 0.76 (95% CI, 0.68-0.83; P= 0.11) in SJLIFE and 0.77 (95% CI, 0.65-0.90) to 0.82 (95% CI, 0.69-0.94; P= 0.073) in CCSS. Conclusions: Inherited polygenic factors contributed significantly to improve CCM prediction over available clinical risk factors and may be of benefit to low-risk survivors for whom routine cardiac surveillance is not currently recommended.